class_docstr: Customized prepare batch callable for trainers or evaluators which support label to be a dictionary.
  Extra items are specified by the `extra_keys` parameter and are extracted from the input dictionary (ie. the batch).
  This assumes label is a dictionary.
  
  Args:
      extra_keys: If a sequence of strings is provided, values from the input dictionary are extracted from
          those keys and passed to the network as extra positional arguments.
code: def __init__(self, extra_keys: Sequence[str]) -> None:
      if len(ensure_tuple(extra_keys)) != 2:
          raise ValueError(
              f"length of `extra_keys` should be 2, get {len(ensure_tuple(extra_keys))}"
          )
      self.prepare_batch = PrepareBatchExtraInput(extra_keys)
  
file_path: MONAI/monai/apps/pathology/engines/utils.py
imports: from __future__ import annotations
  from typing import Any, Sequence
  import torch
  from monai.engines import PrepareBatch, PrepareBatchExtraInput
  from monai.utils import ensure_tuple
  from monai.utils.enums import HoVerNetBranch
label_desc: Use image node_id 1 to create a new PrepareBatchHoVerNet object from inherited base classes: PrepareBatch with example: obj = PrepareBatchHoVerNet(extra_keys)